Guatemala: Selected Issues
Author:
International Monetary Fund. Western Hemisphere Dept.
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Publication Date:
07 Jun 2022
eISBN:
9798400213175
ISBN:
9798400213175
Language:
English
Keywords:
income quintile; inflation differential; income-quintile part; inflation dynamics; part of the analysis; Inflation; Income; Fuel prices
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This analysis aims to characterize some specific features of Guatemala’s recent inflation dynamics, shedding light on the differences in inflation rates across income groups of the population, and the importance of global vs. local factors. First, it shows that the inflation rate for the bottom-income quintile has likely been considerably different from the inflation rate facing the top-income quintile in the post-pandemic period. Second, it suggests that the impact of local food prices in Guatemala appears disconnected from global food prices. Third, it presents evidence that inflation dynamics are mainly driven by local rather than global factors.

Abstract

This analysis aims to characterize some specific features of Guatemala’s recent inflation dynamics, shedding light on the differences in inflation rates across income groups of the population, and the importance of global vs. local factors. First, it shows that the inflation rate for the bottom-income quintile has likely been considerably different from the inflation rate facing the top-income quintile in the post-pandemic period. Second, it suggests that the impact of local food prices in Guatemala appears disconnected from global food prices. Third, it presents evidence that inflation dynamics are mainly driven by local rather than global factors.

Characterizing Recent Inflation Dynamics in Guatemala1

This analysis aims to characterize some specific features of Guatemala’s recent inflation dynamics, shedding light on the differences in inflation rates across income groups of the population, and the importance of global vs. local factors. First, it shows that the inflation rate for the bottom-income quintile has likely been considerably different from the inflation rate facing the top-income quintile in the post-pandemic period. Second, it suggests that the impact of local food prices in Guatemala appears disconnected from global food prices. Third, it presents evidence that inflation dynamics are mainly driven by local rather than global factors.

A. Inflation Across Income Quintiles

1. Global inflation rates have been on the rise since the second half of 2021. Such inflation dynamics, which have affected both advanced as well as emerging and developing economies, have been driven by a strong demand recovery amid continued disruptions of global supply chains, which have put pressure on prices for various products. These pressures, which were already exercising considerable impact on inflation by the beginning of 2022 have been exacerbated by the war in Ukraine, which has led to important increases in the global prices of some commodities, especially fuels and food. In Guatemala, inflationary pressures were contained in 2021, although some signs of external price forces appear in the latest data prints.

2. Rising prices are likely to have had heterogeneous impact across economic sectors and segments of the population. For instance, the series of supply disruptions and increases in energy prices especially affected specific manufacturing industries and energy-intensive sectors. Moreover, the imposition of lockdowns and restrictions to collective transportation resulted in higher prices for specific sectors, such as transport. In turn, these sectoral heterogeneities in price movements have been reflected into different inflation rates across various population groups in light of their different consumption patterns. Moreover, recent rises in food prices have hit the most vulnerable segments of the population especially hard, given the prevalence of food products in their consumption baskets.

3. How different have been inflation rates facing the richer and the poorer segments of the Guatemalan population? This analysis attempts to shed light on this question through the construction of separate consumer price indices for the different income quintiles of the population. The analysis is based on the heterogeneity in consumption patterns across the income quintiles, such as the relatively higher weight of food and other necessities in the consumption basket of the bottom-income quintile or the relatively higher weight of sumptuous products in the consumption basket of the top-income quintile.

CPIs based on Income Quintiles

4. CPIs for different income-quintiles of the Guatemalan population are proxied by the weights employed by the Dominican Republic. While CPIs for the different income segments of Guatemala’s population are not officially available, the analysis makes use of the example from the Dominican Republic, which is the only country in the Central America, Panama, and the Dominican Republic (CAPDR) region that produces official CPIs for the five income quintiles of its population. Given the broad similarities of the economies in the CAPDR region, we assume that the consumption patterns across income quintiles in the Dominican Republic serve as a proxy for the consumption patterns across income quintiles in Guatemala and construct the proxies for income-based CPIs by applying the expenditure weights (12 expenditure divisions) used by the Central Bank of the Dominican Republic.

5. We construct monthly CPI for each income quintile i in Guatemala according to the following equation:

CPIqi=Σj=112(wij*xjwj)=CPIj,2020

Where:

CPIqi represents the Consumer Price Index for income quintile i.

wij represents the weight that expenditure division j has for quintile i for Dominican Republic.

xj represents the weight that expenditure division j has for Guatemalan CPI.

w¯j represents the average weight that expenditure division j has for all quintiles in Dominican Republic.

CPIj,2020 represents the CPI for the expenditure division j in Guatemala considering January 2020 as the base period.

Recent Evolution of Quintile-Based Inflation Rates

6. There has been considerable heterogeneity across inflation rates facing different income quintiles. Figure 1 shows that annual inflation rates differed markedly since the start of the pandemic, particularly between the bottom-income quintile (q1) and the top-income quintile (q5), with the remaining quintiles falling in-between. For instance, the second half of 2020 saw differences in annual inflation of over 3 percentage points between the poorest and richest quintiles.

Figure 1.
Figure 1.

Guatemala: Inflation by Income Quintile

Citation: IMF Staff Country Reports 2022, 165; 10.5089/9798400213175.002.A002

7. Three phases can be identified in the evolution of the inflation rates facing the poorest and richest quintiles since the onset of the pandemic.

  • First, Figure 2 suggests that the bottom-income quintile faced considerably higher inflation than the top-income quintile from the pandemic outbreak until the second quarter of 2021. The difference is due to the decline in fuel prices (relatively more important for the top income quintile) in the initial stages of the pandemic as well as the higher rise in food prices (relatively more important for bottom quintile), due to the series of natural disasters (Eta and Iota) and pandemic-related food disruptions that affected Guatemala in 2020.

  • Second, the economic recovery implied a reversal in 2021, as the fuel price rebound amid a moderation in food prices resulted in higher inflation for top-income quintile relative to the bottom-income quintile (from 2021Q2 to 2021Q4).

  • Third, inflation rates for both income quintiles have increased in recent months against a backdrop of higher food, fuel, and other prices. This development is suggestive that the purchasing power of the poorest has declined more relative to the richest quintile, which could, among others, affect poverty levels.

Figure 2.
Figure 2.

Guatemala: Comparison of Inflation Rates for Bottom-Income and Top-Income Quintiles

Citation: IMF Staff Country Reports 2022, 165; 10.5089/9798400213175.002.A002

8. The different inflation dynamics across these three phases has translated into a CPI gap between the poorest and the richest quintiles. Figure 3 shows that the poorest quintile has faced a higher price level since the pandemic outbreak. While this gap narrowed during 2021, reflecting the reversal in inflation rates described above, it showed some tendency to widen again in the most recent period.

Figure 3.
Figure 3.

Guatemala: Comparison of Price Levels for Bottom-Income and Top-Income Quintiles

Citation: IMF Staff Country Reports 2022, 165; 10.5089/9798400213175.002.A002

Explaining Differences in Inflation Rates between Bottom and Top-Income Quintile

9. Having presented evidence on the different inflation rates for income quintiles, the following analysis examines the factors accounting for these differences. One possibility are the factors driving some of the increase in global inflation such as global food (FDt) and fuel prices (FLt). Formally, the importance of these factors on the inflation differential between the bottom-income and the top-income quintile (dt) is examined using the following simple specification:

dt=α+β1FDt+β2FLt+ϵt(1)

Table 1 presents results from the set of regressions that seek to explain the impact of global fuel and food prices on the differential between the inflation rate of the bottom-income quintile (q1) and the top-income quintile (q5) for Guatemala as well as CAPDR regional peers. There are two key findings from Table 1. First, as expected, higher global fuel prices lead to a lower inflation differential as they affect the inflation rate for top-income quintile q5 relatively more than the one for the bottom-income quintile q1 inflation. This result is significant at the 1 percent level for Guatemala as well as all regional peers. Second, global food prices generally lead to a larger differential for most countries. To the extent that global food prices are related to local country-specific food prices, this result should not be surprising given that food products are relatively more important for the bottom-income quintile than for the top-income quintile. Nonetheless, while global food prices are indeed found to be contributing to a larger q1-q5 inflation differential for the regional peers, the opposite result holds for Guatemala.

Table 1.

Guatemala: Explaining Inflation Differential Between Bottom and Top Income Quintile

article image
Note: Dependent variable is the difference between inflation rates facing the bottom quintile and the top quintile of the income distribution. Global fuel prices are measured through the WTI, and global food prices through the FAO food price index. P-values in parentheses. *** p<0.01, ** p<0.05, * p<0.1

10. What could be explaining this seemingly counterintuitive result? One conjecture is that this result points at a likely “disconnect” between global food prices and local food prices in Guatemala. The next section focuses on exploring the importance of global vs local factors in explaining inflation dynamics in Guatemala more formally.

B. Principal Components Analysis

11. A principal components (PC) analysis is conducted to highlight the limited impact of global factors in explaining inflation dynamics in Guatemala. The above analysis suggests that unlike other countries in the region, the difference in the inflation rates experienced by the top and bottom quintiles is negatively correlated with global food factors. One explanation for this finding is that global factors may not be important drivers of inflation in Guatemala. To evaluate this hypothesis, PC analysis is conducted on Guatemalan and global data. More specifically, PCs are extracted from the overall CPI and twelve inflation divisions in Guatemala.2 We also extract PCs using non-Guatemalan data, namely various inflation measures from the United States (overall CPI, food inflation, energy inflation, core inflation, core goods and core services) and global prices (oil, energy, metal and food, Baltic Price Index) as well as global activity measures (global industrial production and global imports from the Netherlands Bureau for Economic Policy Analysis). Given that monthly data is very volatile, we employ quarterly data from 2012Q1 to 2022Q1.

12. As commonly found in the literature, relatively few PCs explain a large share of the variation of Guatemalan inflation and of the global factors. Figure 4 shows that the first three PCs explain around 65 percent of the variation of the 13 quarterly inflation series, with five PCs (with eigenvalues exceeding 1) explaining around 85 percent. In the case of the global series, the four PCs explain around 85 percent of the variation of all of the series.

Figure 4.
Figure 4.

Guatemala: Principal Components

Citation: IMF Staff Country Reports 2022, 165; 10.5089/9798400213175.002.A002

13. While PCs extracted from Guatemalan data explain a large share of the inflation variance in Guatemala, they do not tend to explain global variables. Moreover, PCs extracted from global variables do not have an important role explaining Guatemalan inflation. The key results are formally shown in Tables 2 and 3, which present the estimates of simple regressions of various inflation subcomponents on the extracted principal components. The regressions are of the form:

xt=α+Σi=1nβiPCi,tj+ϵt(2)
Table 2.

Guatemala: Guatemalan Extracted Components (PCGTM)

article image
Table 3.

Guatemala: PC Extracted Using Non-Guatemalan Variables (PC*)

article image
P-values in parentheses. *** p<0.01, •• p<.05, *p<.1

where x is the variable of interest (inflation in Guatemala or elsewhere), and PC stand for principal components extracted with Guatemala data (j=GTM) or non-Guatemalan data (j=*). The number of PCs selected is up to five for PCGTM, or four, when PC*, consistent with Figure 4. The results shown in Table 2 suggest that the first three PCs largely reflect Guatemala-specific factors since these explain a large variation of CPI and food inflation in Guatemala3 but do not explain much of the variation of energy-related inflation in Guatemala, or inflation in the US or other global inflationary developments. The next two PCs, include global factors (the R2 of US inflation, global oil and food prices increases notably), but provide only some additional explanatory power for Guatemalan CPI and Guatemalan food inflation.

14. Global PCs explain a large share of variation in global variables, but not for Guatemalan inflation. To complement the previous results, similar regressions are estimated for Guatemalan CPI, food and energy inflation, as well as global variables, using the PCs extracted from global variables. The PCs extracted using global variables play an important role in explaining non-Guatemalan data. However, these PCs do not explain much of the variation of Guatemalan inflation variables and only the first PC is significant in the food and energy equations.

C. Concluding Remarks

15. The proxies for quintile-based inflation rates in this analysis pointed at important differences in inflation rates facing the bottom-income quintile and the top-income quintile of the Guatemalan population since the start of the pandemic. Moreover, the income-quintile part of the analysis indicated that the impact of global fuel prices on the inter-quintile inflation differential in Guatemala varies considerably from regional peers, suggesting that the impact of local food prices in Guatemala may be disconnected from global food prices. The principal components part of the analysis provided further support to this conjecture, highlighting the prevalence of local rather than global factors in explaining inflation dynamics in Guatemala.

References

  • IMF (2016), “Guatemala: Selected Issues and Analytical Notes”, IMF Country Report 16/282.

  • IMF (2018), “Guatemala: Selected Issues Paper”, IMF Country Report 18/155.

1

Prepared by Emilio Fernandez-Corugedo, Metodij Hadzi-Vaskov, and Luis Carlos Ibanez Thomae

2

These subcomponents are: food and nonalcoholic beverages; alcoholic beverages and tobacco; clothing and footwear; housing, rent water, electricity and gas; household furnishings and equipment; health; transportation; communication; recreation and culture; restaurants and hotels; education; and Miscellaneous and other goods and services.

3

IMF Country report 16/282 and 18/155 point to a large role of domestic-related factors explaining food inflation developments in Guatemala.

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Cover IMF Staff Country Reports
Guatemala: Selected Issues
Author:
International Monetary Fund. Western Hemisphere Dept.
Volume/Issue:
Volume 2022: Issue 165
Publisher:
International Monetary Fund
ISBN:
9798400213175
ISSN:
1934-7685
Pages:
34
DOI:
https://doi.org/10.5089/9798400213175.002
  • <sup><xref rid="RA002fig01" ref-type="fig">Figure 1.</xref></sup>
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    Figure 1.

    Guatemala: Inflation by Income Quintile

  • <sup><xref rid="RA002fig02" ref-type="fig">Figure 2.</xref></sup>
    View in gallery
    Figure 2.

    Guatemala: Comparison of Inflation Rates for Bottom-Income and Top-Income Quintiles

  • <sup><xref rid="RA002fig03" ref-type="fig">Figure 3.</xref></sup>
    View in gallery
    Figure 3.

    Guatemala: Comparison of Price Levels for Bottom-Income and Top-Income Quintiles

  • <sup><xref rid="RA002fig04" ref-type="fig">Figure 4.</xref></sup>
    View in gallery
    Figure 4.

    Guatemala: Principal Components

Figure 1.

Guatemala: Inflation by Income Quintile
Figure 2.

Guatemala: Comparison of Inflation Rates for Bottom-Income and Top-Income Quintiles
Figure 3.

Guatemala: Comparison of Price Levels for Bottom-Income and Top-Income Quintiles
Figure 4.

Guatemala: Principal Components